The third generation partnership project (3GPP) is directed towards the advancement of technology for radio interfaces and network architectures for wireless communication systems. Multiple-input, multiple-output (MIMO) techniques have been introduced as one of the key approaches to increase the peak data rate, average throughput, and system performance in 3GPP LTE (long term evolution).
DL MU-MIMO (downlink multi-user MIMO) provides a substantial gain in DL communications throughput (i.e. DL capacity) by allowing base stations (in LTE termed evolved Node B or eNB) to transmit information intended for the multiple users on the same physical time-frequency resources. DL MU-MIMO transmission is supported by 3GPP LTE Release 8 (Rel-8) and is a potential technique with some enhancements in LTE-Advanced (Rel-10).
Performance of MIMO techniques, particularly MU-MIMO, is largely dependent on the availability of accurate channel state information (CSI) at the transmitter (CSIT).
The receiver at the UE (User Equipment) estimates the CSI by using reference symbols and could usually obtain an accurate representation of the CSI. Efficient feedback of this CSI determined at the receiver (CSIR) of the UE to the transmitter at the eNB is important for DL MU-MIMO performance, particularly for an FDD (frequency division duplex) system.
Several feedback schemes have been proposed or implemented for reporting CSI from the UE receiver to the transmitter at the eNB on an uplink (UL) channel. These feedback schemes can be characterized as different types of CSI compression techniques.
One scheme is the feedback of a channel covariance matrix (COVM). In practice, the COVM is obtained through averaging channel state information over frequency and/or time domains. It retains all rank information as well as large-scale fading spatial spectrum information, including angle of departure (AOD) and power. Long term averaging may be used to reduce the UL feedback overhead. However, small scale fading information is lost in this case. This approach quantizes each complex element of the COVM and could result in a large feedback overhead.
Another scheme is the principal eigenvector feedback, in which only one (the principal) eigenvector of the channel matrix is reported to the transmitter. This may be viewed as a further compression of the channel COVM. While, the principal eigenvector is a good approximation of the COVM in highly correlated channels, in an uncorrelated channel with higher rank, this approximation will lose information on non-principal ranks. It is similar to COVM feedback scheme, but with fewer elements to be quantized and reported.
In 3GPP LTE Rel-8, a codebook based precoding scheme with limited-CSI feedback is adopted based on a predefined codebook in which a set of codewords is defined based on the Householder (HH) transform. The UE reports the index of the codeword, or so-called precoding matrix index (PMI) at each reporting instance. This scheme has a low feedback overhead compared with the other schemes as mentioned above.
In the codebook based scheme, a UE estimates its channels and quantizes the estimated channels by using a codebook. At the UE a codeword with the best representation of the measured normalized channel is selected from the codebook and the index of the selected codeword, or the PMI, is then fed back from the UE to the eNB transmitter.
The amount of quantization error in the PMI feedback approach depends on codebook size and specific codebook design. Quantization error is more tolerable for single-user MIMO (SU-MIMO), but could degrade MU-MIMO performance significantly. Quantization error could be reduced by using a larger sized codebook, however, it may be impractical to use a very large codebook as it requires a large storage space at both the UE and the eNB as well as more processing time for codebook searching. Moreover, using a large codebook would lead to undesirably large feedback overhead.